Improving Low-Light Image Recognition Performance Based on Image-Adaptive Learnable Module

Seitaro Ono, Yuka Ogino, Takahiro Toizumi, Atsushi Ito, Masato Tsukada, Masato Tsukada

2024

Abstract

In recent years, significant progress has been made in image recognition technology based on deep neural networks. However, improving recognition performance under low-light conditions remains a significant challenge. This study addresses the enhancement of recognition model performance in low-light conditions. We propose an image-adaptive learnable module which apply appropriate image processing on input images and a hyperparameter predictor to forecast optimal parameters used in the module. Our proposed approach allows for the enhancement of recognition performance under low-light conditions by easily integrating as a front-end filter without the need to retrain existing recognition models designed for low-light conditions. Through experiments, our proposed method demonstrates its contribution to enhancing image recognition performance under low-light conditions.

Paper Citation

in Harvard Style

Ono S., Ogino Y., Toizumi T., Ito A. and Tsukada M. (2024). Improving Low-Light Image Recognition Performance Based on Image-Adaptive Learnable Module. In Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP; ISBN 978-989-758-679-8, SciTePress, pages 721-728. DOI: 10.5220/0012459700003660

in Bibtex Style

@conference{visapp24,
author={Seitaro Ono and Yuka Ogino and Takahiro Toizumi and Atsushi Ito and Masato Tsukada},
title={Improving Low-Light Image Recognition Performance Based on Image-Adaptive Learnable Module},
booktitle={Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP},
year={2024},
pages={721-728},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012459700003660},
isbn={978-989-758-679-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP
TI - Improving Low-Light Image Recognition Performance Based on Image-Adaptive Learnable Module
SN - 978-989-758-679-8
AU - Ono S.
AU - Ogino Y.
AU - Toizumi T.
AU - Ito A.
AU - Tsukada M.
PY - 2024
SP - 721
EP - 728
DO - 10.5220/0012459700003660
PB - SciTePress